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One of the great potential benefits of RasterIndex is handling complex transformations where the pixel plane is not aligned with the world plane. A RasterIndex instance can indeed manage the coordinates of the two axes both represented as 2-dimensional lazy arrays.
This is explained more in detail here: https://discourse.pangeo.io/t/example-which-highlights-the-limitations-of-netcdf-style-coordinates-for-large-geospatial-rasters/4140/12, with possible examples including low-level data products (raw acquisition image data with arbitrary GCPs) but also intentional transformations (e.g., rotation) for specific data processing purpose.
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